Broad specificity affinity arrays: a qualitative approach to complex sample discrimination

Abstract

Described is a method for discriminating complex biological samples using an array of discrete biological sensing elements immobilized onto a solid support in which constituents bound to the sensor array is directly determined by measuring the mass increase on the surface; data analysis of said method is performed using neutral network or statical based pattern recognition techniques. In a preferred embodiment the liquid sample is tested for the presence of soluble constituent(s) by contacting said sample with said sensor array under specific conditions, removing unbound sample constituent(s), determining the mass increase on the surface and comparising said mass increase data with a reference standard using pattern recognition software.

Description

[0001]This application is a divisional of U.S. application Ser. No. 09 / 220,822, filed Dec. 24, 1998, which is a continuation of International Application PCT / EP97 / 03317, filed Jun. 24, 1997, which designated the United States, which in turn claims priority under 35 U.S.C.§119 to Swedish Patent Application 9602545-7, filed Jun. 25, 1996.SUMMARY OF THE INVENTION[0002]The invention takes advantage of the ability of neural network and statistical software to analyse complex patterns generated using arrays of discrete sensing elements with intermediate affinities and specificities (broad specificity) as a strategy for complex sample discrimination. Discrete sensing elements with appropriate affinities and specificities are chosen such that each element in the array has an acceptable signal to noise ratio. The informational content obtained from this assay strategy would be meaningless if analysed using conventional methods, i.e. positive vs negative type analysis. Accordingly, a pattern ...

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Benefits of technology

[0003]Thus, instead of quantitating the exact amount of a known compound that has bound to a specific sensing element (as is the case in conventional diagnostics), the bound material is quantitated by determining the increase in thickness or mass on the surface of the sensor. This can be accomplished using a number of nonlabel detection principles including, but not limited to, quartz crystal microbalances, optical techniques such as optoacoustics, reflectometry, ellipsometry and surface plasmon resonance (SPR). An essential aspect of the strategy is the fact that the constituents bound to the sensing elements need not be identified to perform the assay. This makes it possible to use recognition elements with complex interactions such as those found in nature. The samples are discriminated by correlating the values from the entire array using pattern recognition and compared to a reference sample. This increases the speed and reduces the time required to perform assays, thereby reducing costs, all of which are objects of this invention.

[0005]This invention takes advantage of this diversity in order to increase the amount of information that can be obtained, instead of quantitating the exact amount of a particular compound that has bound to a specific lectin as is routinely done in conventional diagnostics. The use of arrays of lectins enables the identification of global changes in complex samples, thereby allowing discrimination. We assume many different substances with a wide range of affinities for a particular sensing element are competing for the recognition sites on the lectins. An additional object of the invention is the ability of the assay strategy to take advantage of as yet unidentified recognition capabilities present on biomolecules. These unidentified recognition elements will provide information that allow the discrimination of samples with unprecedented accuracy and presently not possible with any other diagnostic assay strategy. This complex interplay provides a wealth of data which, due to the rapid development in computer technology and signal processing techniques, can be rapidly analysed. Moreover, the ability of sensing element arrays will grow dramatically as more biomolecules are tested in the assay and their unknown recognition functions become evident.

Problems solved by technology

These changes lead to a series of complex global modifications in the composition and thereby the structure of the carbohydrates.

These unidentified recognition elements will provide information that allow the discrimination of samples with unprecedented accuracy and presently not possible with any other diagnostic assay strategy.

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